code: def get_data(batch_size, test_set, query_set):
      normalizer = transforms.Normalize(
          mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]
      )
  
      transform_test = transforms.Compose(
          [
              transforms.Resize(size=(128, 384), interpolation=1),
              transforms.ToTensor(),
              normalizer,
          ]
      )
  
      test_imgs = ImageTxtDataset(test_set, transform=transform_test)
      query_imgs = ImageTxtDataset(query_set, transform=transform_test)
  
      test_data = gluon.data.DataLoader(
          test_imgs,
          batch_size,
          shuffle=False,
          last_batch="keep",
          num_workers=8,
      )
      query_data = gluon.data.DataLoader(
          query_imgs,
          batch_size,
          shuffle=False,
          last_batch="keep",
          num_workers=8,
      )
      return test_data, query_data
  
file_path: gluon-cv/scripts/re-id/baseline/test.py
imports: from __future__ import print_function, division
  import mxnet
  import numpy
  from mxnet import gluon, nd
  from mxnet.gluon import nn
  from mxnet.gluon.data.vision import transforms
  from networks import resnet18, resnet34, resnet50
  import gluoncv
  from gluoncv.data.market1501.data_read import ImageTxtDataset
  import time, os, sys
  import scipy.io
  from os import path
label_desc: Use image node_id 1 for calling a global function with example usage: get_data(batch_size, test_set, query_set) and returns: test_data,  query_data